1. Field of Invention
The present invention relates to an improved system for obtaining data such as range and intensity information from reflected energy signals. More specifically, the invention concerns a system for scanning a target scene with a laser light source, receiving light signals reflected by the target scene, creating a three-dimensional (3-D) image of the target scene using the reflected signals, and re-sampling the 3-D image to effectively change the perspective of the image.
2. Description of Related Art
Many different systems are known for acquiring electrical images representative of visual target scenes such as landscapes, buildings, military targets, and the like. In one example of such systems, a visual image of a target scene is obtained by a satellite. This type of system is an example of a "passive" system, since the visual image is obtained simply by sensing ambient heat or visible light reflected by the target scene, rather than by sensing reflected light generated by man-made energy sources such as lasers, radar, or other "active" energy sources. In an exemplary satellite system, the satellite detects the ambient light reflected from the target scene, and produces an array, where each element of the array represents the intensity of the reflected ambient light emanating from a designated portion of the target scene. In some applications, this array may be depicted on a multiple pixel screen, where the brightness and/or color of a given pixel may signify the intensity of light reflected by a corresponding portion of the target scene. The array is typically stored in computer memory.
Such systems have been utilized widely for quite some time, and many users have found them to be satisfactory for their purposes. However, when considered in other applications, these systems have a number of limitations. First of all, it may be difficult to interpret the data provided by these systems, since a given level of light intensity may indicate a nearby object with low reflectivity, or a distant object with high reflectivity.
As a result, some users employ passive detection systems in conjunction with "contour maps" that contain detailed terrain elevation data for the target scene. By mathematically correlating a contour map with intensity data obtained by a satellite, it is possible to determine the range in addition to the reflectivity of objects in a target scene. However, this approach has some limitations. More specifically, the resolution of many existing contour maps sometimes exceeds 100 feet, even though some applications may require resolution of six inches or less. Although this problem might be mitigated somewhat by using a custom contour map, the process of constructing such a map may be labor intensive, time consuming, and expensive.
As a result, many people have turned to laser detecting and ranging (LADAR) systems, which use light detecting equipment to record light signals that are generated by a laser light source and reflected by one or more objects in the target scene. Typically, a laser light source transmits laser light signals toward the target scene in a pattern such as a raster, star sequence, or circle sequence. Light detecting equipment, which is often co-located with the laser light source, detects light signals that are reflected by the objects and terrain of the scene. "Objects," for the present discussion, may include fixtures, trees, features of the terrain, moveable items, and other things capable of reflecting or absorbing a laser light signal. With LADAR systems, the shape, orientation, position, and other information about a distant object are derived from the intensity of the light reflected by the object. The range of the object (i.e., distance between the object and the light detecting optics) is derived from the time laser light takes to travel to and from the object.
Raw data collected by a LADAR system is typically processed by electronic processing circuitry such as a computer. During testing or development of the processing circuitry and associated algorithms, a substantial amount of data is collected. Each 3-D image generated by a LADAR system provides information about the target scene from the position of the light detecting optics when the data was sampled. The position of the light detecting optics during scanning of a target scene is the "perspective" of the light detecting optics for that image.
Sometimes after a set of data has been collected, it is desirable to have an image of the same scene, from a different perspective. For instance, it may be useful to generate a series of images of a target scene from different perspectives for use as test input data for a computer controlled guidance or tracking system. By feeding such images to the guidance or tracking system, a test engineer may monitor the system's response under simulated conditions.
A conventional approach to the need for multiple images from diverse perspectives has been to simply reposition the LADAR equipment as desired, re-transmit light signals with the laser source, and re-record the reflected light signals with the light detecting optics. Although this approach may be adequate in some applications, it is limited when used in other contexts. For example, re-positioning the LADAR equipment and re-sampling the data may be expensive and time consuming. Additionally, while it may be desirable to have an image from a certain perspective, it may be impossible in some cases to physically locate the detecting equipment at the required location.
In contrast to the conventional approach discussed above, another approach has been to use a synthetic model of a target scene to generate images of the target scene from different perspectives. With this method, computers are used to mathematically construct a detailed three-dimensional graphical model of the target scene. Then, the target scene may be viewed from any desired perspective by providing the computer with the three-dimensional coordinates of the desired perspective. Although this approach may be helpful in a number of respects, it is limited from the standpoint of complexity and realism. In particular, the synthetic model lacks "real life" aspects, such as electrical or optical noise that would inevitably be present in actual data. Consequently, if a series of synthetic images is generated as test input for a guidance or tracking system, the system's response to noise or other interference generally cannot be determined.